With a Ph.D. in Electrical Engineering and a strong data science and robotics background, I am a skilled and experienced professional in robotics and automation. As a Robotics Software Engineer at Built Robotics, I developed cutting-edge control, estimation, and motion planning algorithms for autonomous excavators. Leveraging my expertise in Python, git, docker, Linux, and unit testing, I contribute to a large codebase, ensuring high-quality and efficient software development processes.

Before my current role, I worked as a Simulation Software Engineer at Westinghouse Electric Corporation, where I applied mathematical modeling and simulations for nuclear fuel, including developing a logistic regression algorithm for predicting nuclear fuel damages. I have also pursued academic excellence, obtaining a Ph.D. in Electrical Engineering focusing on sensor fusion and calibration on embedded platforms from KTH Royal Institute of Technology. I have authored scientific publications and have been involved in teaching and supervising master students in robotics projects.

I am deeply passionate about machine learning and continuously strive to enhance my skills. I hold certificates in Machine Learning Specialization and C/C++ Specialization from Coursera and have completed relevant courses in optimal filtering, estimation theory, matrix algebra, and a summer school on machine learning. I was also part of the prestigious Wallenberg AI, Autonomous Systems and Software Program.

With a solid academic foundation, extensive industry experience, and a constant drive to learn and excel, I am well-equipped to tackle complex challenges and deliver innovative solutions in the field of data science, robotics, automation, and machine learning. If you're seeking a dynamic and results-driven expert to drive your projects forward, let's connect and explore how I can contribute to your success.